=Paper=
{{Paper
|id=Vol-1297/160-165_paper-24
|storemode=property
|title=Исследование как элемент научного дискурса
(Investigation as a Member of Research Discourse)
|pdfUrl=https://ceur-ws.org/Vol-1297/160-165_paper-24.pdf
|volume=Vol-1297
|dblpUrl=https://dblp.org/rec/conf/rcdl/Bunakov14
}}
==Исследование как элемент научного дискурса
(Investigation as a Member of Research Discourse)
==
https://ceur-ws.org/Vol-1297/160-165_paper-24.pdf
Investigation As a Member of Research Discourse*
© Vasily Bunakov
Scientific Computing Department, Science and Technology Facilities Council,
Harwell OX11 0QX, United Kingdom
vasily.bunakov@stfc.ac.uk
Abstract and take a look at the simultaneous circulation of them
in our own research domain of experimental science
Investigations are specific intellectual entities utilizing large research facilities: neutron sources,
that circulate in large research facilities with synchrotrons, and powerful lasers shared by multiple
shared access by multiple research teams; researchers (visiting scientists).
investigations have some common features with
research papers (publications) and can be 2 Facilities research lifecycle and data
included in citation networks. We consider
different approaches to modelling the relations
modelling
between research papers and investigations and
2.1 Facilities science landscape
discuss opportunities for matching these two
members of common research discourse. The Research facilities can be thought of as well-
analysis undertaken can be of interest for equipped hubs where research teams or individual
research centres that consider information researchers come to perform their experiments on their
services based on data and publications own samples. The research facility core is typically
contextualization. represented by a unique scientific instrument: a particle
accelerator, a neutron source, a powerful laser, a
1 Introduction telescope, or a supercomputer that allows detailed
simulation of natural phenomena, or by a few such
The journal articles, e-prints, reports and other
instruments that offer researchers different research
similar artefacts that irrespective of their physical
techniques. The examples include European
manifestation can be seen as derived from their paper-
Synchrotron Radiation Facility (www.esrf.eu), neutron
based “document” ancestors are the well-established
source in The Institut Laue-Langevin (www.ill.eu),
means of research communication and a popular aide
Siberian Synchrotron and Terahertz Radiation Centre
for tracking the state and the trends of research
(http://ssrc.inp.nsk.su/CKP/eng/) or the future Extreme
discourse. The “papers” have clear identity, allow
Light Infrastructure (www.eli-beams.eu).
review (of different kinds) and participate in citation
networks; this supports performing the aforementioned Research conducted in facilities bears characteristics
functions of the quality research communication and of “big science” such as a long-term capital investment,
measurable research tracking; this also makes “papers” permanent support staff, scalable computing
valuable intellectual entities worth capturing in library infrastructure; and “bench science” with individual
catalogues, and worth sharing via advanced information scientists and small research teams that may have
services. specific and short-time research goals. The user
community of European facilities counts tens of
We suggest that other type of intellectual entities,
thousands scientists who pursue different applications:
investigations, have essential features similar to the
crystallography reveals the structures of proteins
document-like entities hence are the natural candidates
important for the development of new drugs; neutron
to supplement “papers” as valuable members of
scattering identifies stresses within engineering
research discourse. We consider the types of relation
components such as turbine blades, and tomography can
between the document-like and investigation entities,
image microscopic details of biological tissues ([1]).
Proceedings of the 16th All-Russian Conference "Digital A business model for user research on large facilities
Libraries: Advanced Methods and Technologies, Digital that emerged a few decades ago has been influenced by
Collections" ― RCDL-2014, Dubna, Russia, October 13–16, the advances in instrumentation and data analysis that
2014. are now more automated and more user friendly than in
early days of facilities a few decades ago. This has led,
* This work is related to the projects of PaNdata collaboration
among other effects, to a lesser significance of the
www.pan-data.eu supported by the EU 7th Framework
Programme for Research and Technological Development. instrumentation “gurus” ([2]), and to the emergence of
The author would like to thank his colleagues in PaNdata for specific services for research and industry that allow
their input for this paper although the views expressed are the users sending their samples for remote investigation
views of the author and not necessarily of the collaboration. according to one of the service plans ([3]).
160
Yet the facilities business model has proved to be Series of Experiments (that altogether
effective and is a foundation for a specific research constitute Investigation with the proclaimed goals):
lifecycle, and for specific information modelling and the user will bring samples, and sometimes an
information services in support of it. additional equipment to the facility, calibrate the
experimental environment and actually take
2.2 Generic research lifecycle measurements
Despite the variety of facilities instruments and Data Archiving: facilities offer high-throughput
experimental techniques, the following distinct stages data collection and archiving services; archiving of raw
are typical across facilities and thus represent a generic data collected in the facility data storage is often a
facilities lifecycle: policy requirement
Research Proposal: the facilities are often Data Analysis: it can be done through multi-
oversubscribed so the researcher (investigator) should layer computing environment where some tools are
justify the value of her research and the suitability of a offered by facilities, and others applied by scientist
particular experimental technique individually
Approval Process: multilateral assessment by Results Publication: journal articles and alike;
the facility, including risk assessment (as the experiment facilities often require the visitor scientist to report back
may involve hazardous materials or techniques) on any publications derived from the experiments.
Experiment Scheduling: allocation of the time This generic lifecycle is illustrated by Figure 1.
slot within a facility operating cycle, and registration of
all visitor scientists
Figure 1. Facilities research lifecycle
2.3 Data modelling effort so far “cores” to the future investigation entities – on the
national research portals, e.g. ISIS neutron and muon
Facilities collect raw experimental data in a variety source (www.isis.stfc.ac.uk) intends to publish the
of formats yet there is a movement towards unification descriptions of all approved proposals on the UK
best represented by NeXuS standard and community common gateway to publicly funded research
around it (www.nexusformat.org). There are of course (http://gtr.rcuk.ac.uk/). The internal representation
data checks and data replication services, as well as format for these entities is going to be CERIF (see under
some recent attempts to form and curate archival www.eurocris.org) that is widely used in the European
packages according to OAIS reference model ([4]). grant information systems.
The aforementioned generic lifecycle gave birth to
the rich CSMD metadata model ([5], [6]) which is 3 Research data in research discourse
implemented, with some modifications, in the popular
ICAT software platform ([7]). 3.1 The modes and purposes of sharing research data
Some facilities started assigning persistent The earlier mentioned NeXuS format, Research
identifiers to datasets ([8]) and there is a recent effort of Objects and persistent identifiers for data present three
having persistent identifiers for other aspects of different modes of sharing research data.
facilities research such as instruments or experimental NeXuS file includes both data and data context
techniques ([9]). (metadata) and thus offers research result as a
The promotion of the research idea through the “package” that can be interpreted by other researchers –
facilities lifecycle has inspired the concept of Research or the same research team in future – with the help of
Objects for facilities science ([10]) that acquire more format-compatible software. It is a responsibility of the
and more detail whilst the investigation proceeds from “package” creator to embed all essential information in
its conceptual stage through the experiment to the there; the boundaries of information context are very
research paper and associated artefacts. well defined (it is literally one data file).
An interesting recent development is the intention of Research Objects suggest the enrichment of
some facilities to start publishing the descriptions of the information according to a specific model while the
approved research proposals (grants) – that are the intellectual entity moves through the research lifecycle;
161
this implies that there is a “creator” to the model and the The Figure 2 illustrates provenance relations
“curator” of intellectual entity on each phase of between investigations and research papers that are a
lifecycle; the boundaries of intellectual entity are more foundation for appropriate “citations”.
flexible (it may be an aggregation of various
components) but are still well-defined.
The supply of nothing more but persistent identifiers
for data, perhaps associated with some moderate
contextual description (metadata), implies the paradigm
of “open world” where intellectual entities can be
deliberately constructed by various agents, hence there
are no clear (predefined) boundaries to the entities, and
virtually everyone can be considered a data “curator”.
Sharing data or information, however, is not the end
in itself and can be considered as a means to empower Figure 2. Research provenance chain
research discourse, to supply some intellectual entities
Similarities between investigation and research
into it. So quite often, when people speak of “research
paper as intellectual entities are summarized in the
data” they actually mean intellectual entities where data
Table 1.
may be just a component, or something associated with
a “quantum” of research discourse. Table 1. Common features of investigations and
This can be illustrated by observations over DataCite research papers.
(www.datacite.org) – a platform that proclaimed goal is
supplying data with dereferencaeble persistent Feature / aspect Publication Investigation
identifiers (well-formed DOIs). The data centres who (research paper)
actually use DataCite in fact tend to assign DOIs not to Is an intellectual Yes Yes
datasets but to “quantums” of research discourse, e.g. to entity
doctoral theses (that may of course contain some data Is a subject of peer Yes Yes
but is not the data per se). In case of facilities science, review (via proposal
we observe that DataCite DOIs are in fact approval)
dereferenceable to the landing Web pages that contain Can cite all Yes Yes
descriptions of investigations which are, as we significant
explained it earlier, the series of experiments performed intellectual entities
with a certain research goal on the assigned instrument of research discourse
within a dedicated timeslot. Citation chains exist Yes Yes
So when a researcher cites “data” via DataCite DOI, (steps of discourse
observed
she in fact quite often cites an intellectual entity – which
can be a paper or something else, e.g. event (such as an Universal identifiers Yes Yes
earthquake) in geophysics, or investigation in the case available
of facilities science. 1 This attitude towards “data” DOIs
assignment is only natural as what researchers tend to Looking into what intellectual entities can refer to
cite may not be “data” per se but certain identifiable what other intellectual entities (with the inclusion of
elements of research discourse. datasets and software – which may or may not bear a
clear identity) suggests the asymmetry in the direction
3.2 The place of investigation and the place of data in of references so that e.g. a research paper can cite a
facilities research discourse dataset but not vice versa:
Investigation as an intellectual entity bears some Table 2. Cross-references of intellectual entities
features that are common with traditional research
paper. Indeed, an investigation proposal is peer- References Paper Investi- Dataset Software
reviewed; investigation can be cited from papers by the (“from” row gation
“to” column)
well-formed DOI and from other investigations, too, as
when a researcher submits proposal, she refers to the Paper Yes Yes Yes Yes
relevant past publications and past investigations. 2 Investigation Yes Yes Yes Yes
Dataset No Yes Yes Yes (e.g.
simulation)
1
Examples of dereferenceable “data” DOIs that in fact
resolve in investigation or research paper descriptions: Software Yes (e.g. No Yes Yes
to paper
http://dx.doi.org/10.5286/ISIS.E.24066298
about
http://dx.doi.org/10.5167/UZH-27029 algorithm)
2
Looking into the ICAT database for ISIS facility indicates
the existence of investigation “chains” when the next
investigation refers to the previous one, with as many as four
investigations in a row undertaken in the last 10 years.
162
In fact, research discourse in facilities science splits investigations lifecycle) and those in the institutional
into the two distinctive layers that can be called “research library catalogues.
per se” and “data management”; this is illustrated by To estimate the viability of automated techniques,
Figure 3. we tried to match the bibliographic records for the
papers that were the “input” to the investigations
performed on ARGUS muon spectrometer. 3 We
managed to visually identify the small number of the
well-formed bibliographic records in the institutional
repository that for sure match the corresponding poorly-
formed ARGUS bibliographic records. We then applied
different modifications to the ARGUS records in
combination with measuring the Levenstein distance
Figure 3. Directions of typical references and two ([13]) between them and those in the library catalogue.
layers of research discourse The first experiments suggest that bibliographic
records from two systems: ePubs which is the
The two layers only loosely interact with each other institutional papers repository and ISIS ICAT which is
and the bottom one can be considered a service layer in the data catalogue supported by ISIS neutron and muon
support of the top one, despite recent attempts to facility, can be successfully matched if we measure
promote a view that information departments can play a Levenstein distance between modified bibliographic
role of data curation units, hence expanding their remit records. A particular pretty simple technique could be
from the mere support of information technology to the extraction and normalization of the numeric
catering for richer tastes of researchers interested in components from the bibliographic record (volume,
semantic representation of information and in its pages and year), measuring distances between such
sensible reuse ([11]). normalized extracts – in effect, between two strings
with only numbers in them – then playing with the
3.3 Problems, challenges and opportunities
threshold (the particular Levenstein distance) that
The above analysis contributes to modelling of allows to distinguish between matches and non-
research discourse in facilities science with the matches. This technique was tried out via bespoke Java
suggestion that data and software should play a modest software module and is illustrated by Table 3.
(supportive) role compared to research papers and well- The technique tuning, including the measurements
defined investigations. Different information models of precision and recall, should be done with the larger
that can be applied to the same facilities research numbers of bibliographic records; there is about a
discourse. One of them is the model based on Research thousand records in ICAT data catalogue that have
Objects ([10]) that suggest the “enrichment” of the core bibliographic components – candidates for matching
Investigation entity while it moves down the facilities them with bibliographic records in ePubs papers
research lifecycle illustrated by Figure 1 – turning into a repository. Yet it has to be understood that mere
rich aggregation of data, data context (metadata), and matching bibliographic records is just the first step in
software. Another view is seeing research discourse as what we aspire to: a reasonably automated technique for
“grid” composed of provenance chains similar to that in linking investigations to research papers in situations
Figure 2; the Research Activity model ([12]) offers a where there are no bibliographic records catalogued for
basic semantic means to support this view. investigations, only investigations textual descriptions
Irrespective of what of the two models we adhere to, and other metadata.
they are likely to use the same techniques, e.g. for There are more than ten thousand papers in ePubs
matching research papers with investigations. repository that are marked up by the librarians as having
One problem here is that, despite it is a requirement of relation to ISIS neutron and muon facility with no
facilities to submit the “input” to the investigation proposal indication which investigation (series of experiments) or
and then the “output” of it in terms of research papers that instrumental work they actually relate to. For the majority
led to the idea of the experiment, or have been resulted of these papers, there are no corresponding bibliographic
from it – there is no good curation of these bibliographic records in the facility investigations catalogue; hence
records, or a clear requirement for their format. On the other techniques are required to match the papers to
other hand, when the institutional library eventually and investigations. We consider decomposition of, on one
independently collects the facility output in the form of hand, the bibliographic records from ePubs institutional
research papers, they do it in a systematic way with good repository and, on the other hand, the investigation
coverage and according to the best cataloguing practice but descriptions from the ISIS investigations database into
there is no record of the investigation that the paper has the corresponding elements, then looking into distances
been resulted from as there is no requirement to capture it between elements with the further aggregation of them
in the bibliographic record, also the investigation is often into sensible metrics. The analysis of bibliographic
mentioned only implicitly in the paper. So if we want more records and investigation descriptions suggests the
context for the research papers and for the investigations, following elements as the candidates for mutual mapping:
there is a task of matching bibliographic records coming
from facilities User Office (the unit that looks after 3
http://www.isis.stfc.ac.uk/instruments/argus/argus6461.html
163
Table3. Matching bibliographic records in ICAT data Another opportunity for the validation of the
catalogue and ePubs papers repository (ARGUS case) investigations-to-publications matching technique will
be looking into descriptions of research proposals
Levenstein (grants) in the research information portals. For ISIS
distance
Levenstein Levenstein between
facility, it will be Gateway to Research portal
distance distance “numeric” (http://gtr.rcuk.ac.uk/) that is about to start collecting
ICAT ePubs
Reference reference
between full between parts with the investigation proposals in a systematic manner so that
bibliographic “numeric” year sometime after the investigations are over, they will be
references parts normalized
and the last
supplemented by the submission of research papers
page removed resulted from them. It will be possible then to use the
Pratt et al, Phys. Phys Rev newer investigations accompanied by papers resulted
Rev. Lett. 96, Lett 96 from them (as submitted by the researchers themselves)
17 0 0
247203 (2006) 247203 for the calibration of the automated matching technique
(2006)
Lancaster et al, Phys Rev
that can be applied to the large corpus of past
Phys. Rev B73, B 73 investigations and research papers.
24 1 1
020410(R) 020410 Validated via two independent sources of
(2005) (2006)
Blundell and J Phys
bibliography: ePubs institutional repository and
Pratt, J. Phys.: Condens (forthcoming) records in the Gateway to Research
Condens. Matter Matter 16 portal, the automated matching technique may become
16, R771 (2004) R771- 30 3 0 a useful tool for research contextualization and for
R828
(2004)
enrichment of the existing records in publications and
data catalogues.
M.T.F.Telling J Phys
and Condens
Apart from matching research papers with
S.H.Kilcoyne, Matter 19 investigations, an interesting theme for further research
Electron transfer 2 026221 could be looking into the cases of “indirect citations”
in dextran, J. (2007) 81 6 6 when (see Figure 2) one research paper does not directly
Phys.: Condens.
Matter 19 No 2
cite another one but there is an identifiable connection
(17 January from one to another through the intermediary
2007) investigation; or the similar consideration from the
J Tomkinson and Phys investigations network perspective where one
M.T.F Telling, Chem investigation does not explicitly refer to another but
Ammonium ions Chem
in alkali metal Phys 8 they are in fact connected through the intermediary
halide crystals: 4434- 113 12 5 research paper(s). Discovering these sorts of “indirect
Tunnelling and 4440 citations” may contribute to the development of
spin relaxation, (2006) alternative metrics for measuring research output, in
PCCP 2006 8 38
4434 addition to traditional paper citation metrics.
4 Conclusion
The mentioned massive of records in the ISIS ICAT
data catalogue (about a thousand of them) – for which the Our analysis indicates that Investigation in facilities
association with ePubs papers catalogue can be established science is an intellectual entity that has a clear identity,
via the earlier outlined bibliographic records matching is involved in structured information exchange and
technique – can be used for the validation of automated bears some essential features similar to traditional
matching between investigation metadata records and research papers. There are various opportunities for the
(more than ten thousand) bibliographic records for all ISIS information modelling and for the formation of links
instruments. Then validation by the researchers themselves between investigations and other intellectual entities,
will be required, as well as some technical means in namely research papers that can be either an input to the
support of that validation – such as online polls. investigation, or an outcome of it.
This study can be considered an analysis and a
roadmap that precede the scalable experiments on the
information contextualization in the domain of facilities
science. It is also a call for information practitioners to
share their views on the research information
contextualization and on the role of various intellectual
entities in their research domains, as the popular notion
of “data” and its widely accepted importance may
sometimes misrepresent the actual content of research
discourse where other domain-specific intellectual
entities could be more appropriate for sensible
Figure 4. Mapping research papers bibliography to information management and for measuring research
investigations metadata output.
164
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